Bubble sort performs significantly better on nearly sorted lists because its design allows it to detect when no swaps are needed during a pass. When a list is already mostly in order, few or no swaps are required, and the algorithm can terminate early. This is made possible by using a flag (often called swapped) that monitors whether any elements were exchanged in the current pass. If the flag remains false by the end of the pass, the algorithm concludes the list is sorted and stops. In the best-case scenario, where the list is already completely sorted, bubble sort only needs one full pass to verify order, making the time complexity O(n). This is a major improvement over the worst-case performance of O(n²). However, even with early termination, bubble sort is still not as efficient as other adaptive algorithms like insertion sort when dealing with nearly sorted data, but it does benefit noticeably compared to fully unsorted input.

Bubble sort is considered a stable sorting algorithm because it preserves the relative order of records with equal values. That means if two elements have the same key, the one that appeared first in the original list will also appear first in the sorted list. This characteristic is particularly important when sorting complex data structures, such as records or objects with multiple fields. For instance, if you have a list of students sorted by exam score, and several students have the same score, a stable sort will ensure that their order from the original list (perhaps based on name or ID) remains unchanged. In applications where secondary attributes are meaningful or where multiple sorting passes are performed (e.g. first by date, then by name), stability ensures consistency and predictability in output. Bubble sort achieves this naturally because it only swaps elements when the left one is greater than the right, not when they are equal.

In bubble sort, the number of comparisons is fixed for each pass and only reduces slightly as the algorithm progresses, while the number of swaps depends on how disordered the list is. Specifically, comparisons always occur between adjacent elements across the unsorted portion of the list, which leads to approximately n² comparisons in the worst case. However, swaps only occur when elements are out of order. This means a list that is already nearly sorted might still involve many comparisons but very few swaps. Conversely, a completely reverse-ordered list will trigger a swap on nearly every comparison. Swaps are more computationally expensive than comparisons because they involve reassigning memory values, especially for large or complex data structures. Therefore, while bubble sort’s inefficiency is often attributed to the number of comparisons, the cost of frequent swaps contributes significantly to its poor performance, particularly when working with lists of objects or records rather than simple numbers.

Bubble sort is especially useful in teaching because it offers a clear, visual process that is easy to follow. Each pass through the list involves a predictable sequence of comparisons and swaps, which makes it simple to represent on screen, paper, or in interactive simulations. The concept of "bubbling" the largest item to the end of the list is intuitive, and the results of each pass are easy to observe. Furthermore, the algorithm’s control structure is straightforward, typically involving just two nested loops and a conditional statement. This simplicity allows students to focus on the fundamental ideas of sorting and iteration without being distracted by complex logic. It also reinforces basic programming skills such as array indexing, loops, and variable use. Many online sorting visualisers use bubble sort as their introductory example because it shows incremental progress after each step, making it ideal for understanding algorithmic thinking, debugging, and performance analysis at a beginner level.

Yes, bubble sort can be easily adapted to sort in descending order by simply reversing the comparison condition. In the standard version for ascending order, the algorithm swaps two adjacent elements if the left element is greater than the right. To sort in descending order, you change this condition so that it swaps elements if the left element is less than the right. This adjustment ensures that the largest elements are "bubbled" to the beginning of the list rather than the end. The rest of the algorithm remains unchanged — it still involves nested loops, repeated passes, and stops early if no swaps occur in a pass. This adaptability is one of bubble sort’s strengths: it doesn’t require significant rewriting to change the sorting order. Although bubble sort still remains inefficient in terms of performance regardless of sort direction, the ease of modifying it makes it useful for demonstrating how algorithms can be customised for different problem requirements.